Job Title:

Data & Analytics Solutions Architect (Azure

+ Snowflake

+ Cortex)

Location:

NJ/NYC Employment Type:

Full-time Job Description:

Data & Analytics Solutions Architect (Azure

+ Snowflake

+ Cortex)

Must Have Technical/Functional Skills:

14+ years of experience in Enterprise Data Architecture, Azure Data Platforms, Snowflake, Data Engineering, and Cloud Modernization. Proven experience in Enterprise Solution architecture using Azure, Snowflake, Cortex and related technology components across the Data to Insights end to end value chain. Strong hands-on expertise in Azure Data Services, Snowflake Data Cloud, Snowflake Cortex AI, Python, SQL, Spark, and Data Modeling. Proven experience designing and implementing enterprise data platforms, Data Lakehouse architectures, Data Warehousing, and modern analytics solutions. Strong understanding of Snowflake Architecture, including virtual warehouses, Snowpipe, streams & tasks, data sharing, workload management, performance tuning, and cost optimization. Experience building AI-enabled analytics solutions using Snowflake Cortex AI Functions, Cortex Search, Cortex Analyst, Cortex Agents, GenAI, and RAG-based solutions. Expertise in Data Engineering including ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and DataOps practices. Strong knowledge of Enterprise Data Architecture, including data models, data products, semantic layers, lakehouse and warehouse patterns, and master/reference data management. Experience implementing Security, Governance, and Compliance controls including IAM/RBAC, encryption, privacy, masking, auditability, retention, and responsible AI practices. Proven experience leading architecture definition, HLD/LLD preparation, NFR assessment, migration planning, technical governance, and production readiness activities. Experience supporting cloud transformation initiatives, solutioning, RFP responses, effort estimation, and client-facing architecture discussions. Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements. Bachelor s degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline. Preferred certifications in Azure Solutions Architecture, Azure Data Engineering, Snowflake (SnowPro), Data Management, Enterprise Architecture, Security, or AI/ML.

Roles & Responsibilities:

Engage with business and technology stakeholders to understand data, analytics, AI, and cloud transformation requirements. Define end-to-end architecture for modern data and AI platforms using Azure, Snowflake, and Snowflake Cortex AI. Design secure, scalable, and resilient data platforms integrating Azure Data Services, Azure Data Lake Storage, and Snowflake. Architect batch, near-real-time, and streaming data pipelines supporting enterprise reporting, analytics, and AI use cases. Design Snowflake account, database, schema, virtual warehouse, data-sharing, and workload-management patterns. Develop AI-enabled analytics solutions using Cortex AI Functions, Cortex Search, Cortex Analyst, and Cortex Agents. Establish data governance, security, metadata, lineage, observability, privacy, and responsible AI controls. Lead data platform modernization, migration, and cloud transformation initiatives. Define reference architectures, engineering standards, reusable patterns, CI/CD, and DataOps practices. Provide technical leadership across solution design, implementation, testing, migration, deployment, and production readiness. Conduct architecture reviews, identify risks and dependencies, and guide delivery teams on mitigation actions. Drive performance, reliability, and cost optimization across Azure and Snowflake environments. Collaborate with data engineers, AI specialists, platform teams, and client stakeholders to deliver production-ready solutions. Support solutioning, RFP responses, effort estimation, technical presentations, demonstrations, and client workshops. Mentor architects and engineers and contribute to technical assessments, capability development, and knowledge sharing. Develop reusable accelerators, implementation playbooks, and best practices for Azure, Snowflake, and Cortex AI solutions